Correlation b/w dependent vars.(food loss and food waste)
## # A tibble: 3 × 4
## rowname food_waste_kg liquid_waste_kg solid_waste_kg
## * <chr> <dbl> <dbl> <dbl>
## 1 food_waste_kg 1 0.97 0.88
## 2 liquid_waste_kg 0.97 1 0.73
## 3 solid_waste_kg 0.88 0.73 1
## # A tibble: 3 × 4
## rowname food_waste_kg liquid_waste_kg solid_waste_kg
## <chr> <dbl> <dbl> <dbl>
## 1 food_waste_kg 0 9.85e-100 5.27e-52
## 2 liquid_waste_kg 9.85e-100 0 2.94e-28
## 3 solid_waste_kg 5.27e- 52 2.94e- 28 0

Correlation b/w independent vars.
## # A tibble: 9 × 10
## rowname temp_c humi_p prcp_mm fulls halfs takeouts customers liquors sales
## * <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 temp_c 1 0.094 -0.035 0.25 0.094 0.11 0.24 0.066 0.27
## 2 humi_p 0.094 1 0.35 -0.043 -0.15 -0.03 -0.065 -0.23 -0.11
## 3 prcp_mm -0.035 0.35 1 -0.19 -0.097 -0.087 -0.16 -0.18 -0.16
## 4 fulls 0.25 -0.043 -0.19 1 0.33 0.15 0.92 0.33 0.8
## 5 halfs 0.094 -0.15 -0.097 0.33 1 0.19 0.62 0.15 0.5
## 6 takeouts 0.11 -0.03 -0.087 0.15 0.19 1 0.2 0.2 0.54
## 7 customers 0.24 -0.065 -0.16 0.92 0.62 0.2 1 0.32 0.84
## 8 liquors 0.066 -0.23 -0.18 0.33 0.15 0.2 0.32 1 0.46
## 9 sales 0.27 -0.11 -0.16 0.8 0.5 0.54 0.84 0.46 1
## # A tibble: 9 × 10
## rowname temp_c humi_p prcp_mm fulls halfs takeouts customers liquors
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 temp_c 0 2.34e-1 6.57e-1 1.47e- 3 2.36e- 1 1.62e- 1 2.44e- 3 4.02e- 1
## 2 humi_p 2.34e-1 0 5.74e-6 5.85e- 1 5.28e- 2 7.07e- 1 4.1 e- 1 2.8 e- 3
## 3 prcp_mm 6.57e-1 5.74e-6 0 1.65e- 2 2.21e- 1 2.74e- 1 3.86e- 2 2.47e- 2
## 4 fulls 1.47e-3 5.85e-1 1.65e-2 0 1.58e- 5 6.14e- 2 4.63e-65 2.27e- 5
## 5 halfs 2.36e-1 5.28e-2 2.21e-1 1.58e- 5 0 1.35e- 2 1.07e-18 5.79e- 2
## 6 takeouts 1.62e-1 7.07e-1 2.74e-1 6.14e- 2 1.35e- 2 0 1.18e- 2 1.32e- 2
## 7 custome… 2.44e-3 4.1 e-1 3.86e-2 4.63e-65 1.07e-18 1.18e- 2 0 3.12e- 5
## 8 liquors 4.02e-1 2.8 e-3 2.47e-2 2.27e- 5 5.79e- 2 1.32e- 2 3.12e- 5 0
## 9 sales 6.34e-4 1.74e-1 4.45e-2 6.76e-37 2.14e-11 9.41e-14 1.32e-44 5.46e-10
## # ℹ 1 more variable: sales <dbl>

Correlation b/w independent vars.
## # A tibble: 6 × 7
## rowname temp_c humi_p prcp_mm customers liquors sales
## * <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 temp_c 1 0.094 -0.035 0.24 0.066 0.27
## 2 humi_p 0.094 1 0.35 -0.065 -0.23 -0.11
## 3 prcp_mm -0.035 0.35 1 -0.16 -0.18 -0.16
## 4 customers 0.24 -0.065 -0.16 1 0.32 0.84
## 5 liquors 0.066 -0.23 -0.18 0.32 1 0.46
## 6 sales 0.27 -0.11 -0.16 0.84 0.46 1
## # A tibble: 6 × 7
## rowname temp_c humi_p prcp_mm customers liquors sales
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 temp_c 0 0.234 0.657 2.44e- 3 4.02e- 1 6.34e- 4
## 2 humi_p 0.234 0 0.00000574 4.1 e- 1 2.8 e- 3 1.74e- 1
## 3 prcp_mm 0.657 0.00000574 0 3.86e- 2 2.47e- 2 4.45e- 2
## 4 customers 0.00244 0.41 0.0386 0 3.12e- 5 1.32e-44
## 5 liquors 0.402 0.0028 0.0247 3.12e- 5 0 5.46e-10
## 6 sales 0.000634 0.174 0.0445 1.32e-44 5.46e-10 0
## Correlation computed with
## • Method: 'pearson'
## • Missing treated using: 'pairwise.complete.obs'


Correlogram
Cross-Correlation
